<h2>DESCRIPTION</h2>

<em>v.lidar.growing</em> is the second of three steps to filter LiDAR data. 
The filter aims to recognize and extract attached and detached object 
(such as buildings, bridges, power lines,  trees, etc.) in order to create 
a Digital Terrain Model. 
<br>
<br>
The modules identifies which is the internal area of every object on a 
LiDAR point surface. The classification categories from 
<em>v.lidar.edgedetection</em> are now rasterized. For each cell, it is 
evaluated if it (the cell) contains a point with double impulse (difference 
between the first and last pulse greater than a given threshold). Starting 
from cells classified as OBJECT and with only one pulse all linked cells 
are selected and a convex hull algorithm is applied to them. Simultaneously, 
the mean of the corresponding heights (mean edge height) are computed. 
Points inside the convex hull are classified as OBJECT if their height is 
greater than or equal to the previously mean computed edge height. This 
last step is done only in case of high planimetric resolution.

<h2>NOTES</h2>

The input data should be the output result of the <em>v.lidar.edgedetection</em>,
module. Otherwise, it goes to error! The output of this module will be 
the input of <em>v.lidar.correction</em> module. The output will be a vector 
map which points are pre-classified as:
<br>
<br>
TERRAIN SINGLE PULSE (cat = 1, layer = 2)
<br>
TERRAIN DOUBLE PULSE (cat = 2, layer = 2)
<br>
OBJECT SINGLE PULSE (cat = 3, layer = 2)
<br>
OBJECT DOUBLE PULSE (cat = 4, layer = 2)
<br>
<br>

The final result of the whole procedure (<em>v.lidar.edgedetection</em>, 
<em>v.lidar.growing</em>, <em>v.lidar.correction</em>) will be a point 
classification in the same categories as above.

<h2>EXAMPLES</h2>

<h3>Basic region growing procedure</h3>
<div class="code"><pre>
v.lidar.growing input=edge output=growing first=firstpulse
</pre></div>

<h2>SEE ALSO</h2>

<em>
<a href="v.lidar.edgedetection.html">v.lidar.edgedetection</a>,
<a href="v.lidar.correction.html">v.lidar.correction</a>,
<a href="v.surf.bspline.html">v.surf.bspline</a>,
<a href="v.surf.rst.html">v.surf.rst</a>,
<a href="v.in.lidar.html">v.in.lidar</a>,
<a href="v.in.ascii.html">v.in.ascii</a>
</em>

<h2>AUTHOR</h2>
Original version of program in GRASS 5.4:
<br>
Maria Antonia Brovelli, Massimiliano Cannata, Ulisse Longoni and Mirko Reguzzoni
<p>
Update for GRASS 6.X:
<br>
Roberto Antolin and Gonzalo Moreno

<h2>REFERENCES</h2>

Antolin, R. et al., 2006. Digital terrain models determination by LiDAR 
technology: Po basin experimentation. Bolletino di Geodesia e Scienze 
Affini, anno LXV, n. 2, pp. 69-89.
<p>
Brovelli M. A., Cannata M., Longoni U.M., 2004. LIDAR Data Filtering and 
DTM Interpolation Within GRASS, Transactions in GIS, April 2004,  vol. 8, 
iss. 2, pp. 155-174(20), Blackwell Publishing Ltd.
<p>
Brovelli M. A., Cannata M., 2004. Digital Terrain model reconstruction in 
urban areas from airborne laser scanning data: the method and an  example 
for Pavia (Northern Italy). Computers and Geosciences 30 (2004) pp.325-331
<p>
Brovelli M. A. and Longoni U.M., 2003. Software per il filtraggio di dati 
LIDAR, Rivista dell?Agenzia del Territorio, n. 3-2003, pp. 11-22 (ISSN 1593-2192).
<p>
Brovelli M. A., Cannata M. and Longoni U.M., 2002. DTM LIDAR in area urbana, 
Bollettino SIFET N.2, pp. 7-26.
<p>
Performances of the filter can be seen in the
<a href="http://www.itc.nl/isprswgIII-3/filtertest/MainDoc.htm">ISPRS WG III/3 Comparison of Filters</a> 
report by Sithole, G. and Vosselman, G., 2003. 
<br>

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